Book Chapter
Showing results 1 - 6 out of 6
Journal Articles
Showing results 41 - 60 out of 302
2024
Sarvari, H., Baghbaderani, A. B., Chan, D. W. M., & Beer, M. (2024). Determining the significant contributing factors to the occurrence of human errors in the urban construction projects: A Delphi-SWARA study approach. Technological Forecasting and Social Change, 205, Article 123512. https://doi.org/10.1016/j.techfore.2024.123512
Sarvari, H., Asaadsamani, P., Olawumi, T. O., Chan, D. W. M., Rashidi, A., & Beer, M. (2024). Perceived barriers to implementing building information modeling in Iranian Small and Medium-Sized Enterprises (SMEs): a Delphi survey of construction experts. Architectural Engineering and Design Management, 20(3), 673-693. https://doi.org/10.1080/17452007.2024.2329687
Shi, Y., Behrensdorf, J., Zhou, J., Hu, Y., Broggi, M., & Beer, M. (2024). Network reliability analysis through survival signature and machine learning techniques. Reliability engineering & system
safety, 242, Article 109806. https://doi.org/10.1016/j.ress.2023.109806
Shi, Y., Chai, R., & Beer, M. (2024). Novel gradient-enhanced Bayesian neural networks for uncertainty propagation. Computer Methods in Applied Mechanics and Engineering, 429, Article 117188. https://doi.org/10.1016/j.cma.2024.117188
Shi, Y., & Beer, M. (2024). Physics-informed neural network classification framework for reliability analysis. Expert systems with applications, 258, Article 125207. Advance online publication. https://doi.org/10.1016/j.eswa.2024.125207
Song, J., Cui, Y., Wei, P., Rashki, M., Zhang, W., & Beer, M. (2024). Directional filter combined with active learning for rare failure events. Computer Methods in Applied Mechanics and Engineering, 428, Article 117105. https://doi.org/10.1016/j.cma.2024.117105
Wang, R., Chen, G., Liu, Y., & Beer, M. (2024). Computational modeling of near-fault earthquake-induced landslides considering stochastic ground motions and spatially varying soil. Engineering structures, 316, Article 118580. https://doi.org/10.1016/j.engstruct.2024.118580
Wang, Z. W., Lu, X. F., Zhang, W. M., Fragkoulis, V. C., Zhang, Y. F., & Beer, M. (2024). Deep learning-based prediction of wind-induced lateral displacement response of suspension bridge decks for structural health monitoring. Journal of Wind Engineering and Industrial Aerodynamics, 247, Article 105679. https://doi.org/10.1016/j.jweia.2024.105679
Wang, R., Ouyang, J., Fragkoulis, V. C., Liu, Y., & Beer, M. (2024). Experimental model updating of slope considering spatially varying soil properties and dynamic loading. Earthquake Engineering and Resilience, 3(1), 33-53. https://doi.org/10.1002/eer2.70
Wang, R., Li, S., Liu, Y., Hu, X., Lai, X., & Beer, M. (2024). Peridynamics-based large-deformation simulations for near-fault landslides considering soil uncertainty. Computers and geotechnics, 168, Article 106128. https://doi.org/10.1016/j.compgeo.2024.106128
Wang, L., Hu, Z., Dang, C., & Beer, M. (2024). Refined parallel adaptive Bayesian quadrature for estimating small failure probabilities. Reliability Engineering and System Safety, 244, Article 109953. https://doi.org/10.1016/j.ress.2024.109953
Wang, C., Beer, M., Faes, M. G. R., & Feng, D. C. (2024). Resilience Assessment under Imprecise Probability. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10(2), Article 04024025. https://doi.org/10.1061/AJRUA6.RUENG-1244
Yang, L., Zhang, X., Lu, Z., Fu, Y., Moens, D., & Beer, M. (2024). Reliability evaluation of a multi-state system with dependent components and imprecise parameters: A structural reliability treatment. Reliability Engineering and System Safety, 250, Article 110240. https://doi.org/10.1016/j.ress.2024.110240
Yang, J. S., Chen, J. B., & Beer, M. (2024). Seismic topology optimization considering first-passage probability by incorporating probability density evolution method and bi-directional evolutionary structural optimization. Engineering structures, 314, Article 118382. https://doi.org/10.1016/j.engstruct.2024.118382
You, Z., Miao, H., Shi, Y., & Beer, M. (2024). Improving the performance of low-frequency magnetic energy harvesters using an internal magnetic-coupled mechanism. Journal of applied physics, 135(8), Article 084101. https://doi.org/10.1063/5.0195091
Yuan, P., Yuen, K. V., Beer, M., Cai, C. S., & Yan, W. (2024). A non-iterative partitioned computational method with the energy conservation property for time-variant dynamic systems. Mechanical Systems and Signal Processing, 209, Article 111105. https://doi.org/10.1016/j.ymssp.2024.111105
Zhang, Y., Dong, Y., & Beer, M. (2024). rLSTM-AE for dimension reduction and its application to active learning-based dynamic reliability analysis. Mechanical Systems and Signal Processing, 215, Article 111426. https://doi.org/10.1016/j.ymssp.2024.111426
Zhao, Y., Sun, B., Bi, S., Beer, M., & Moens, D. (2024). A sub-convex similarity-based model updating method considering multivariate uncertainties. Engineering structures, 318, Article 118752. Advance online publication. https://doi.org/10.1016/j.engstruct.2024.118752
Zheng, Z., Beer, M., & Nackenhorst, U. (2024). Efficient stochastic modal decomposition methods for structural stochastic static and dynamic analyses. International Journal for Numerical Methods in Engineering, 125(12), Article e7469. https://doi.org/10.1002/nme.7469
Zhou, T., Guo, T., Dang, C., & Beer, M. (2024). Bayesian reinforcement learning reliability analysis. Computer Methods in Applied Mechanics and Engineering, 424, Article 116902. https://doi.org/10.1016/j.cma.2024.116902